Downloaded from genome.cshlp.org on September 23, 2021 - Published by Cold Spring Harbor Laboratory Press Research Comparative transcriptomics of primary cells in vertebrates Tanvir Alam,1 Saumya Agrawal,2 Jessica Severin,2 Robert S. Young,3,4 Robin Andersson,5 Erik Arner,2 Akira Hasegawa,2 Marina Lizio,2 Jordan A. Ramilowski,2 Imad Abugessaisa,2 Yuri Ishizu,6,13,14 Shohei Noma,2 Hiroshi Tarui,6,13 Martin S. Taylor,4 Timo Lassmann,2,7 Masayoshi Itoh,8 Takeya Kasukawa,2 Hideya Kawaji,2,8 Luigi Marchionni,9 Guojun Sheng,10 Alistair R.R. Forrest,2,11 Levon M. Khachigian,12 Yoshihide Hayashizaki,8 Piero Carninci,2 and Michiel J.L. de Hoon2 1College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar; 2RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; 3Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh EH8 9AG, United Kingdom; 4MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom; 5The Bioinformatics Centre, Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark; 6RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama 230-0045, Japan; 7Telethon Kids Institute, University of Western Australia, Perth, WA 6009, Australia; 8RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako 351-0198, Japan; 9Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA; 10International Research Center for Medical Sciences (IRCMS), Kumamoto University, Kumamoto 860-0811, Japan; 11Harry Perkins Institute of Medical Research, and the Centre for Medical Research, University of Western Australia, QEII Medical Centre, Perth, WA 6009, Australia; 12Vascular Biology and Translational Research, School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, NSW 2052 Australia Gene expression profiles in homologous tissues have been observed to be different between species, which may be due to differences between species in the gene expression program in each cell type, but may also reflect differences in cell type composition of each tissue in different species. Here, we compare expression profiles in matching primary cells in human, mouse, rat, dog, and chicken using Cap Analysis Gene Expression (CAGE) and short RNA (sRNA) sequencing data from FANTOM5. While we find that expression profiles of orthologous genes in different species are highly correlated across cell types, in each cell type many genes were differentially expressed between species. Expression of genes with products in- volved in transcription, RNA processing, and transcriptional regulation was more likely to be conserved, while expression of genes encoding proteins involved in intercellular communication was more likely to have diverged during evolution. Conservation of expression correlated positively with the evolutionary age of genes, suggesting that divergence in expres- sion levels of genes critical for cell function was restricted during evolution. Motif activity analysis showed that both pro- moters and enhancers are activated by the same transcription factors in different species. An analysis of expression levels of mature miRNAs and of primary miRNAs identified by CAGE revealed that evolutionary old miRNAs are more likely to have conserved expression patterns than young miRNAs. We conclude that key aspects of the regulatory network are con- served, while differential expression of genes involved in cell-to-cell communication may contribute greatly to phenotypic differences between species. [Supplemental material is available for this article.] Vertebrate organisms consist of hundreds of cell types, with more characterization has been supplemented by molecular approaches than 400 cell types defined in human (Vickaryous and Hall 2006). such as molecular fingerprinting (Arendt 2008) as well as genome- Traditionally, cell types have been defined by their tissue of origin wide profiling of the transcriptome of primary cells (The FANTOM as well as by their cellular phenotypes including morphology, Consortium and the RIKEN PMI and CLST (DGT) 2014). To this staining properties, enzyme histochemistry, and cell surface mark- end, the Human Cell Atlas initiative aims to comprehensively er recognition by antibodies (Vickaryous and Hall 2006). Cell type define human cell types by performing transcriptome analysis in single cells on a massive scale (Regev et al. 2017). Evolution of anatomy is thought to primarily depend on the 13After RIKEN’s reorganization in 2018, the RIKEN Center for Life evolution of gene expression patterns and regulation, rather than Science Technologies, Division of Genomic Technologies continued the evolution of the encoded protein sequences (Britten and as part of the RIKEN Center for Integrative Medical Sciences. 14Present address: RIKEN Center for Brain Science, Wako 351-0198, Davidson 1971; King and Wilson 1975). While comparative Japan Corresponding author: [email protected] Article published online before print. Article, supplemental material, and publi- © 2020 Alam et al. This article, published in Genome Research, is available un- cation date are at http://www.genome.org/cgi/doi/10.1101/gr.255679.119. der a Creative Commons License (Attribution 4.0 International), as described at Freely available online through the Genome Research Open Access option. http://creativecommons.org/licenses/by/4.0/. 30:951–961 Published by Cold Spring Harbor Laboratory Press; ISSN 1088-9051/20; www.genome.org Genome Research 951 www.genome.org Downloaded from genome.cshlp.org on September 23, 2021 - Published by Cold Spring Harbor Laboratory Press Alam et al. studies have shown that gene expression programs in matching pressed if their dominant promoter was located in a genomic re- tissues are largely conserved between species (Su et al. 2002; gion that did not have an orthologous genome sequence in the − Chan et al. 2009; Brawand et al. 2011; Merkin et al. 2012), many human genome (Fisher combined P <10 100) (Fig. 3B; Supplemen- genes were found to be differentially expressed (Su et al. 2002; tal Fig. S1), suggesting that gain or loss of promoter sequence re- Lin et al. 2014; Yue et al. 2014). Although such expression differ- gions during evolution contributes to the emergence of gene ences between human and mouse for specific genes may be due expression differences between species. in part to differences in cell type composition of the analyzed tis- We hypothesized that genes critical for cellular functioning sues (Breschi et al. 2017), little overlap was found in terms of differ- would both be more conserved and their expression patterns less entially expressed genes between human and mouse in dynamic diverged during evolution, and indeed we found the expression studies of primary cells during erythropoiesis (Pishesha et al. levels of evolutionarily older genes to be more conserved (Fisher − 2014) and of primary macrophages upon stimulation by lipopoly- combined P <10 100) (Fig. 4A; Supplemental Fig. S2). Gene saccharide (Schroder et al. 2012) or by glucocorticoid (Jubb et al. Ontology analysis of differentially expressed genes showed that 2016). Collectively, these findings suggest that also in matching genes with products involved in transcription, RNA processing, primary cells many genes are differentially expressed between spe- and transcriptional regulation were more likely to have conserved cies. As cells with an identical cellular phenotype may display dis- expression levels, whereas genes encoding proteins localized to the tinct and disparate molecular phenotypes, the question of what plasma membrane and extracellular space as well as signaling pro- key transcriptomic features define a cell type is raised (Arendt teins were most likely to be differentially expressed (Fig. 4B; et al. 2016). Supplemental Table S3). This suggests that the transcriptional pro- The confounding effects of cell type composition in tissue- gram in each cell tends to be conserved during evolution, while based studies can be avoided by comparing the transcriptome of genes in the periphery of the transcriptional regulatory network, different species in homologous primary cells. Here, we present a especially those involved in cellular communication, tend to comparative analysis of genome-wide expression in vertebrate spe- diverge in expression. cies profiled in FANTOM5 (The FANTOM Consortium and the As an independent confirmation, we applied integrative cor- RIKEN PMI and CLST (DGT) 2014; Lizio et al. 2017a,b) to elucidate relation analysis (Parmigiani et al. 2004) by first calculating the patterns of gene expression conservation during evolution. correlations across cell types between all genes for human and mouse separately, and then the correlation across orthologous Results genes between corresponding rows in these two correlation matri- ces. This yielded the correlation-of-correlations, or integrative cor- The FANTOM5 collection contains Cap Analysis Gene Expression relation coefficient, as a measure of the degree of expression (CAGE) data for three primary cell types in human, mouse, rat, conservation during evolution for each gene. We then ranked dog, and chicken, and for an additional 12 cell types in human genes based on their integrative correlation coefficient and per- and mouse only (Supplemental Table S1). We identified 15,538, formed gene set enrichment analysis to identify biological process- 14,915,